Pre-screened and vetted.
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps
Senior Data Engineer specializing in cloud data platforms and real-time pipelines
Mid-level Data Engineer specializing in cloud lakehouse and streaming pipelines
Director-level Data & AI Leader specializing in enterprise transformation
“Built Cigna Health’s risk-based management/monitoring system used as a primary product for pharmaceutical clients, supporting clinical trials and utilized during the COVID-19 pandemic. Currently running a community-based startup (details kept proprietary) and is open to executive roles or joining a strong team with a clear path to success, evaluating opportunities via ROI.”
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Junior AI/ML & Cloud Software Engineer specializing in LLM applications
“AI engineer (2+ years; pursuing an online MS at UIUC) who has shipped an AI-powered voice screening platform end-to-end on GCP with strong production monitoring and measurable hiring-process impact (80% reduction in unqualified pass-through; ~50+ hours saved per role). Also built and deployed an AWS-based context-aware hybrid search system using OpenSearch as a vector store, and has hands-on experience with multi-agent LLM orchestration (ReAct) and structured-output guardrails.”
Mid-Level Full-Stack Software Engineer specializing in cloud-native data platforms
“LLM/agentic systems practitioner who specializes in moving customer prototypes into production within microservices environments, emphasizing reliability, latency, security, and measurable success metrics. Experienced in real-time troubleshooting using logs/traces and in enabling adoption through hands-on developer workshops (including live coding in Java Spring Boot) and pre-sales POCs that address technical objections and integration risk.”
Junior Full-Stack/ML Engineer specializing in LLM applications and cloud deployment
“Full-stack developer with capstone and project experience delivering production-ready systems in unstructured environments, including a Faculty Tracking system for real departmental use. Strong in React performance debugging (re-render optimization with useMemo), Prisma-backed multi-database setups (MySQL local / SQL Server production on a UCI Health VM), and end-user support workflows that feed back into improved Help documentation.”
Intern Software Engineer specializing in FinTech and AI platforms
“Systems-focused engineer who built an OS kernel with multithreading, priority scheduling, system calls, and synchronization primitives, and debugged race conditions end-to-end. While not yet hands-on with ROS/SLAM, they clearly connect low-level concurrency and scheduling decisions to deterministic, reliable robotics-style real-time workloads.”
Intern Machine Learning Engineer specializing in LLMs, RAG, and vision-language systems
“Robotics ML/software engineer focused on Vision-Language-Action control for 7-DoF robots, replacing tokenized action decoding with continuous regression heads (including a logit-weighted expectation approach) to improve stability and real-time behavior. Strong in ROS1/ROS2 systems integration and debugging closed-loop manipulation issues via latency instrumentation, QoS-aware distributed messaging, and sim-to-real validation using Gazebo/Unity, Docker, and CI pipelines.”
Junior Machine Learning Engineer specializing in data pipelines and applied AI
“Built a production AI agent for phishing fraud detection using n8n orchestration, Claude (Sonnet 4/MCP), VirusTotal, and JavaScript formatting to generate and deliver email-based reports via Gmail. Has experience evaluating detection accuracy against known examples, iterating via feedback, and presenting AI solutions to non-technical teams.”
Intern Software Engineer specializing in distributed systems and backend infrastructure
“Backend engineer with deep experience building event-driven logistics systems (orders, warehouse execution, real-time delivery tracking) using Spring Boot/PostgreSQL/Redis and strong observability (Prometheus/Grafana). Led a zero-downtime migration from monolithic MySQL to a sharded architecture for ~2M users with dual-write, checksum validation, and fast auto-rollback, and has strong security expertise including PostgreSQL RLS for multi-tenant SaaS and robust OAuth/JWT handling.”
“Built and deployed a live LLM-powered platform that takes a LinkedIn job URL + resume and generates job-specific resumes and personalized outreach at scale, with production-grade logging/monitoring/retries on Vercel + Railway. Experienced with agent orchestration (AWS Bedrock/Strands, LangGraph, CrewAI) and rigorous AI workflow testing, plus stakeholder-facing prototypes like data lineage/metadata and NL-to-SQL + dashboard generation.”
Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics
“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”
Mid-level Data Analyst & AI Practitioner specializing in ML, LLMs, and analytics platforms
“Data Analyst at U.S. Cellular who built production LLM solutions, including a Tableau-embedded chatbot that converts natural language questions into Oracle SQL and returns actionable KPI insights for non-technical users. Also authored MAD-CTI, a multi-agent LLM system for dark web hacker forum threat intelligence (published in IEEE Access) that outperformed single-agent approaches by 14%.”
Intern Software Engineer specializing in systems and full-stack web development
“Open-source contributor to a JavaScript visualization library who focused on runtime/rendering performance—eliminating unnecessary full redraws via memoization and diff-based updates validated with Chrome profiling. Also strengthened the project’s developer experience by adding TypeScript definitions, writing practical documentation, building minimal example apps, and handling community issues with reproducible debugging and public fixes.”
Senior AI/ML Data Scientist specializing in NLP, computer vision, and MLOps
“Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.”
Senior Data Scientist specializing in GenAI, LLM systems, and production ML
Intern Data Scientist / Software Engineer specializing in ML, computer vision, and cloud
Mid-level Data Scientist specializing in machine learning, analytics, and cloud data pipelines
Senior Full-Stack Software Engineer specializing in Python/Django and modern JavaScript
Mid-level Backend/Platform Engineer specializing in distributed systems and data platforms
Mid-level Machine Learning Engineer specializing in MLOps and applied AI